scholarly journals A Low-cost Normalized Difference Vegetation Index (NDVI) Payload for Cubesats and Unmanned Aerial Vehicles (UAVs)

2018 ◽  
Author(s):  
Steven Hard
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Low Cost ◽  
Aerial Vehicles

scholarly journals UAV Detection of Sinapis arvensis Infestation in Alfalfa Plots Using Simple Vegetation Indices from Conventional Digital Cameras

2020 ◽  
Vol 2 (2) ◽  
pp. 206-212 ◽  
Author(s):  
Luis Fernando Sánchez-Sastre ◽  
Mª Auxiliadora Casterad ◽  
Mónica Guillén ◽  
Norlan Miguel Ruiz-Potosme ◽  
Nuno M. S. Alte da Veiga ◽  
...  
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Low Cost ◽  
Vegetation Indices ◽  
Digital Cameras ◽  
Site Specific ◽  
Aerial Vehicles ◽  
Ndvi Index ◽  
Weed Cover

Unmanned Aerial Vehicles (UAVs) offer excellent survey capabilities at low cost to provide farmers with information about the type and distribution of weeds in their fields. In this study, the problem of detecting the infestation of a typical weed (charlock mustard) in an alfalfa crop has been addressed using conventional digital cameras installed on a lightweight UAV to compare RGB-based indices with the widely used Normalized Difference Vegetation Index (NDVI) index. The simple (R−B)/(R+B) and (R−B)/(R+B+G) vegetation indices allowed one to easily discern the yellow weed from the green crop. Moreover, they avoided the potential confusion of weeds with soil observed for the NDVI index. The small overestimation detected in the weed identification when the RGB indices were used could be easily reduced by using them in conjunction with NDVI. The proposed methodology may be used in the generation of weed cover maps for alfalfa, which may then be translated into site-specific herbicide treatment maps.

scholarly journals Detecting Individual Tree Attributes and Multispectral Indices Using Unmanned Aerial Vehicles: Applications in a Pine Clonal Orchard

2020 ◽  
Vol 12 (24) ◽  
pp. 4144
Author(s):  
José Luis Gallardo-Salazar ◽  
Marín Pompa-García
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Vegetation Indices ◽  
Field Measurements ◽  
Tree Level ◽  
Individual Tree ◽  
Basal Diameter ◽  
Crown Diameter ◽  
Aerial Vehicles

Modern forestry poses new challenges that space technologies can solve thanks to the advent of unmanned aerial vehicles (UAVs). This study proposes a methodology to extract tree-level characteristics using UAVs in a spatially distributed area of pine trees on a regular basis. Analysis included different vegetation indices estimated with a high-resolution orthomosaic. Statistically reliable results were found through a three-phase workflow consisting of image acquisition, canopy analysis, and validation with field measurements. Of the 117 trees in the field, 112 (95%) were detected by the algorithm, while height, area, and crown diameter were underestimated by 1.78 m, 7.58 m2, and 1.21 m, respectively. Individual tree attributes obtained from the UAV, such as total height (H) and the crown diameter (CD), made it possible to generate good allometric equations to infer the basal diameter (BD) and diameter at breast height (DBH), with R2 of 0.76 and 0.79, respectively. Multispectral indices were useful as tree vigor parameters, although the normalized-difference vegetation index (NDVI) was highlighted as the best proxy to monitor the phytosanitary condition of the orchard. Spatial variation in individual tree productivity suggests the differential management of ramets. The consistency of the results allows for its application in the field, including the complementation of spectral information that can be generated; the increase in accuracy and efficiency poses a path to modern inventories. However, the limitation for its application in forests of more complex structures is identified; therefore, further research is recommended.

scholarly journals Comparison of Sentinel-2 and UAV Multispectral Data for Use in Precision Agriculture: An Application from Northern Greece

Drones ◽  
2021 ◽  
Vol 5 (2) ◽  
pp. 35
Author(s):  
Nikolaos Bollas ◽  
Eleni Kokinou ◽  
Vassilios Polychronos
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Precision Agriculture ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Northern Greece ◽  
Multispectral Data ◽  
Aerial Vehicles ◽  
The Difference ◽  
Uav Images ◽  
Sentinel 2

The scope of this work is to compare Sentinel-2 and unmanned aerial vehicles (UAV) imagery from northern Greece for use in precision agriculture by implementing statistical analysis and 2D visualization. Surveys took place on five dates with a difference between the sensing dates for the two techniques ranging from 1 to 4 days. Using the acquired images, we initially computed the maps of the Normalized Difference Vegetation Index (NDVI), then the values of this index for fifteen points and four polygons (areas). The UAV images were not resampled, aiming to compare both techniques based on their initial standards, as they are used by the farmers. Similarities between the two techniques are depicted on the trend of the NDVI means for both satellite and UAV techniques, considering the points and the polygons. The differences are in the a) mean NDVI values of the points and b) range of the NDVI values of the polygons probably because of the difference in the spatial resolution of the two techniques. The correlation coefficient of the NDVI values, considering both points and polygons, ranges between 83.5% and 98.26%. In conclusion, both techniques provide important information in precision agriculture depending on the spatial extent, resolution, and cost, as well as the requirements of the survey.

scholarly journals Regrowth and ornamental traits of bermudagrass fertilized with sewage sludge

2020 ◽  
Vol 26 (3) ◽  
pp. 390-398
Author(s):  
Philippe Solano Toledo Silva ◽  
Alessandro Reinaldo Zabotto ◽  
Patrick Luan Ferreira dos Santos ◽  
Matheus Vinícius Leal do Nascimento ◽  
Armando Reis Tavares ◽  
...  
Keyword(s):  
Sewage Sludge ◽  
Soil Solution ◽  
Digital Image Analysis ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Low Cost ◽  
Aesthetic Aspect ◽  
Positive Correlations ◽  
The Aesthetic ◽  
Ornamental Traits

Abstract The sewage sludge is a low-cost material and sustainable alternative to substitute chemical fertilizers on ornamental lawns and gardens. Thus, the objective was to evaluate the effects of the application of sewage sludge on the regrowth and ornamental traits of DiscoveryTM bermudagrass. The experiment was carried out during the fall/winter of 2019. The turf was removed and left the soil exposed for a new grass regrowth. The treatments applied were 0, 357, 714, 1,071 and 1,428 g m-2 sewage sludge spread evenly on the lawn in a single dose. The evaluations were carried out after 120 days and the soil solution (EC and NO3 -), Normalized difference vegetation index, root length, root + rhizome + stolon + leaves volume and digital image analysis were evaluated. The results showed that the increase of sewage sludge positively influenced the turfgrass development, both in the aesthetic aspect and on bermudagrass regrowth. The soil solution can show that the sludge increased the electrical conductivity and NO3- ions; however, it did not hinder the development of the lawn, even having positive correlations between these variables and the biometric evaluations of the plant. It is concluded that the dose of 1,428 g m-2 presented the best results for the evaluated characteristics, being the recommended one for use in the fertilization of bermudagrass DiscoveryTM.

scholarly journals Eyes in the Sky: Assessing the Feasibility of Low-Cost, Ready-to-Use Unmanned Aerial Vehicles to Monitor Primate Populations Directly

2019 ◽  
Vol 91 (1) ◽  
pp. 69-82
Author(s):  
Brandon P. Semel ◽  
Sarah M. Karpanty ◽  
Faramalala Francette Vololonirina ◽  
Ando Nantenaina Rakotonanahary
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Low Cost ◽  
Aerial Vehicles

scholarly journals Model-Based Autonomous Navigation with Moment of Inertia Estimation for Unmanned Aerial Vehicles

Sensors ◽  
2019 ◽  
Vol 19 (11) ◽  
pp. 2467 ◽  
Author(s):  
Hery Mwenegoha ◽  
Terry Moore ◽  
James Pinchin ◽  
Mark Jabbal
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Navigation System ◽  
Process Model ◽  
Unscented Kalman Filter ◽  
Low Cost ◽  
Moment Of Inertia ◽  
Model Parameters ◽  
Main Process ◽  
Model Based ◽  
Aerial Vehicles

The dominant navigation system for low-cost, mass-market Unmanned Aerial Vehicles (UAVs) is based on an Inertial Navigation System (INS) coupled with a Global Navigation Satellite System (GNSS). However, problems tend to arise during periods of GNSS outage where the navigation solution degrades rapidly. Therefore, this paper details a model-based integration approach for fixed wing UAVs, using the Vehicle Dynamics Model (VDM) as the main process model aided by low-cost Micro-Electro-Mechanical Systems (MEMS) inertial sensors and GNSS measurements with moment of inertia calibration using an Unscented Kalman Filter (UKF). Results show that the position error does not exceed 14.5 m in all directions after 140 s of GNSS outage. Roll and pitch errors are bounded to 0.06 degrees and the error in yaw grows slowly to 0.65 degrees after 140 s of GNSS outage. The filter is able to estimate model parameters and even the moment of inertia terms even with significant coupling between them. Pitch and yaw moment coefficient terms present significant cross coupling while roll moment terms seem to be decorrelated from all of the other terms, whilst more dynamic manoeuvres could help to improve the overall observability of the parameters.

scholarly journals Accurate Landing of Unmanned Aerial Vehicles Using Ground Pattern Recognition

Electronics ◽  
2019 ◽  
Vol 8 (12) ◽  
pp. 1532 ◽  
Author(s):  
Jamie Wubben ◽  
Francisco Fabra ◽  
Carlos T. Calafate ◽  
Tomasz Krzeszowski ◽  
Johann M. Marquez-Barja ◽  
...  
Keyword(s):  
Pattern Recognition ◽  
Unmanned Aerial Vehicles ◽  
High Precision ◽  
Low Cost ◽  
Target Position ◽  
Flight Behavior ◽  
Ground Pattern ◽  
Aerial Vehicles ◽  
Exact Position ◽  
Precision Landing

Over the last few years, several researchers have been developing protocols and applications in order to autonomously land unmanned aerial vehicles (UAVs). However, most of the proposed protocols rely on expensive equipment or do not satisfy the high precision needs of some UAV applications such as package retrieval and delivery or the compact landing of UAV swarms. Therefore, in this work, a solution for high precision landing based on the use of ArUco markers is presented. In the proposed solution, a UAV equipped with a low-cost camera is able to detect ArUco markers sized 56 × 56 cm from an altitude of up to 30 m. Once the marker is detected, the UAV changes its flight behavior in order to land on the exact position where the marker is located. The proposal was evaluated and validated using both the ArduSim simulation platform and real UAV flights. The results show an average offset of only 11 cm from the target position, which vastly improves the landing accuracy compared to the traditional GPS-based landing, which typically deviates from the intended target by 1 to 3 m.

scholarly journals Operational Framework for Rapid, Very-high Resolution Mapping of Glacial Geomorphology Using Low-cost Unmanned Aerial Vehicles and Structure-from-Motion Approach

2019 ◽  
Vol 11 (1) ◽  
pp. 65 ◽  
Author(s):  
Marek W. Ewertowski ◽  
Aleksandra M. Tomczyk ◽  
David J. A. Evans ◽  
David H. Roberts ◽  
Wojciech Ewertowski
Keyword(s):  
High Resolution ◽  
Unmanned Aerial Vehicles ◽  
Structure From Motion ◽  
Low Cost ◽  
Control Point ◽  
Glacial Geomorphology ◽  
High Resolution Mapping ◽  
Aerial Vehicles ◽  
Resolution Mapping ◽  
Very High

This study presents the operational framework for rapid, very-high resolution mapping of glacial geomorphology, with the use of budget Unmanned Aerial Vehicles and a structure-from-motion approach. The proposed workflow comprises seven stages: (1) Preparation and selection of the appropriate platform; (2) transport; (3) preliminary on-site activities (including optional ground-control-point collection); (4) pre-flight setup and checks; (5) conducting the mission; (6) data processing; and (7) mapping and change detection. The application of the proposed framework has been illustrated by a mapping case study on the glacial foreland of Hørbyebreen, Svalbard, Norway. A consumer-grade quadcopter (DJI Phantom) was used to collect the data, while images were processed using the structure-from-motion approach. The resultant orthomosaic (1.9 cm ground sampling distance—GSD) and digital elevation model (7.9 cm GSD) were used to map the glacial-related landforms in detail. It demonstrated the applicability of the proposed framework to map and potentially monitor detailed changes in a rapidly evolving proglacial environment, using a low-cost approach. Its coverage of multiple aspects ensures that the proposed framework is universal and can be applied in a broader range of settings.

scholarly journals Method for Estimating Solar Energy Potential Based on Photogrammetry from Unmanned Aerial Vehicles

Electronics ◽  
2020 ◽  
Vol 9 (12) ◽  
pp. 2144
Author(s):  
Jose Eduardo Fuentes ◽  
Francisco David Moya ◽  
Oscar Danilo Montoya
Keyword(s):  
Solar Energy ◽  
Unmanned Aerial Vehicles ◽  
3D Model ◽  
Low Cost ◽  
Atmospheric Conditions ◽  
Solar Panels ◽  
Energy Potential ◽  
Aerial Vehicles ◽  
3D Data ◽  
Surface Models

This study presents a method to estimate the solar energy potential based on 3D data taken from unmanned aerial devices. The solar energy potential on the roof of a building was estimated before the placement of solar panels using photogrammetric data analyzed in a geographic information system, and the predictions were compared with the data recorded after installation. The areas of the roofs were chosen using digital surface models and the hemispherical viewshed algorithm, considering how the solar radiation on the roof surface would be affected by the orientation of the surface with respect to the sun, the shade of trees, surrounding objects, topography, and the atmospheric conditions. The results show that the efficiency percentages of the panels and the data modeled by the proposed method from surface models are very similar to the theoretical efficiency of the panels. Radiation potential can be estimated from photogrammetric data and a 3D model in great detail and at low cost. This method allows the estimation of solar potential as well as the optimization of the location and orientation of solar panels.

Sign in / Sign up

Export Citation Format

Share Document